I was laid off as a senior product manager in December of 2025. I’ve been looking for a new job in clean energy (which is supposedly “having a moment” due to data centers) since then. There is no “jobs boom”. There are certainly job openings — black holes into which you can lodge your resume. Occasionally, multiple rounds of interviews that go nowhere. I’ve been paying my bills as an art fabricator and live event electrician, the kinds of blue collar jobs that are supposed to make up for the destruction of “knowledge work”. The work is inconsistent, and the pay is less than half of what I made before. There is no “jobs boom”, of any kind.
I don't think this is entirely true: let's just say the jobs boom is unevenly distributed. There are definitely more openings than there were a year ago, but it is also now much more of a challenge to effectively market yourself as a person in tech.
On the one hand there is the problem that every job posting is flooded with hundreds of bogus AI resumes which, if they are not outright fabrications, stretch the truth enough to make it hard to tell who is qualified and who is not.
Anecdotally, it seems to me like directly applying to jobs is a waste. You either have to find some way to attract recruiter outreach, or network with people who can get you a foot in the door.
> There are certainly job openings — black holes into which you can lodge your resume
And recruiters are just flat out creating fake job listings on Indeed, with no pretense, describing them as "an opportunity to register your interest in similar roles", and Indeed are allowing it.
No they are not, try to change jobs and if you can't or takes a really long time you know this is some of the finest baloney.
And no, it's not creating a lot of jobs, one one of the kind that will be destroyed by AI no, and that's the point... you built something that removes the pricey laywer, software developer, insurance policy writer, designer, etc... and replace it with a ONE TIME go work under the sun with no ac in the middle of nowhere as a contractor of the contractor of the contractor...
So sure, I'm a dooms-scroll-lover, sure the 10000000 new part time possitions with no benefit of any kind will be the biggest work boom EVER... you will just go to compete with all the other people already doing that... and you know what happens when there is a queue of 100 to flip burgers or "highly technical non AI replaceable work like weld or electricist" right??
"you built something that removes the pricey laywer, software developer, insurance policy writer, designer"
This statement is untrue. The people have the judgement, the AI does the rote work. The rest is marketing fluff and/or leadership fumbles. You can't get rid of judgement (unless of course leadership is fumbling).
With more AI, you got more radiology requests, and more radiologists [1] and better health results due to more abundant measurement. There is no evidence that the same isn't happening to the rest of the professions. And to support it all, we have more infrastructure construction (datacenters).
This is the textbook basics of a growing economy with growing productivity, even though it feels paradoxical [2]
Jevons Paradox doesn't say more radiologist will have more work and will be paid at the same price, it says that there will be more work for radiologists because now they are paid less and because of that people is able to afford more radiologists.
"This statement is untrue. The people have the judgement, the AI does the rote work. The rest is marketing fluff and/or leadership fumbles. You can't get rid of judgement (unless of course leadership is fumbling)."
Let me refine it more... now the same lawyer/marketing/software engineer can work just approving the work of AI, reviewing it's correct so the exact same lawyer/marketing/software engineer can now perform X more times the amount of work they previously did, IF we don't triple the amount of work, then the rules of "free market" means that offer now exceeds by X the demand and you can now depress wages as much as you want because you can fire (x-1)/x of the people doing the work and the pool of people willing or needing to do that is increased.
This does not contradict at all what I stated above.
The ultimate proof of this is how much the "calculator people" now earns now that calculators were created... and for reference this old ad about the effect of calculators on the number of engineers
"radiologists because now they are paid less and because of that people is able to afford more radiologists."
But again, the opposite is happening. Radiologist salaries are up 9% YoY [1]. And you can now get your radiology done more cheaply [2]. Literal win-win.
Radiologists are not human calculators, neither are lawyers, accountants or insurance adjusters. As we learned very quickly, their job is judgement and human relationships and you can't cut that out
You did correctly lay out that if you can't grow your business by increasing demand, you are shrinking. And yes shrinking leads to layoffs regardless of AI.
Very cliched now but: You are not being replaced by AI, you are being replaced by someone who's using AI, who is more productive with it. But specifically, this is true for individuals and company-wide. Less productive organizations will be pushed out if they can't lower their prices and meet the increasing demand, and the only way they do that for modern white-collar work (not rote 1950's calculator churning) is to hire more AI-ready staff.
FWIW, The IBM ad is literal marketing fluff. More engineers were employed in the immediate aftermath of the mainframe than anytime before.
EDIT: I'm not trying to argue with you, I'm trying to show you things most headline news refuses to show because it's boring and counter-narrative. Shoutout to the economist.
E.g. take the radiology example. In the past people would not have been sent to a radiologist due to resource constraints.
But because of AI you now more capacity - therefore there is an INCREASE in radiology requests.
And this is going to be the common theme - there are lots of things that people are doing right now has an implicit constraint. AI will unlock new capacity so we will see MORE of it -> this will actually create a bizarre scenario of a labour shortage in many respects.
I know that's not what Amodei and Altman want to hear but... ha.
THis is why people are so bad at predictions - they look at one variable move and forget the rest / many 'unknowns' they did not foresee.
if you're going by anecdata, myself and a few of my colleagues (senior ics) switched jobs relatively easily for a solid pay increase within the last year. definitely easier than post-covid
engineering (hardware, software) and data center construction are going through a boom cycle right now and will eventually bust, and so on and so forth
And the robots are just a few years away. I thought that spatial reasoning was going to be a lot harder for AI, but Astra is showing that progress on that front is also moving very rapidly.
I think the world has gone too crazy to make any such claim. They could be decades away, they could be a year away.
Remember that it doesn't have to be necessarily better than a human, it just needs to make economical sense. A robot that fails 20% of the time but costs 0.10$/h to run beats a person for many tasks.
"humanoid" robots are as relevant to commercial robotics as AGI to LLM, that is, not at all. As long as they can move on wheels and operate 2 hands (doesn't matter how many fingers), the application is huge already.
AI has completely broken interviewing as well. The asks I am getting in the few interviews I can achieve are schizophrenic.
They have pretty uniformly wanted me to demonstrate using AI but then freak out and interrogate me for every prompt and then want me to demonstrate I can do the task by hand. And that’s only after getting through the AI run filtering that gives a different score everytime your unchanged resume is run through the model.
It’s dark times for employment currently unless you’ve got a rare nepotism path.
It was always better to find job via recommendations. Both for companies and candidates.
Old leetcode style interviews were no better at identifying good candidates for given job.
I don’t know if those companies are doing it for the right reasons but I’ve implemented a policy of showing me that you can do the job manually as well.
The reason being that if you can’t then you probably can’t tell when the AI is wrong.
My company is strictly Cybersecurity/IR though so that may vary with other specialties.
If the interview was specifically about doing it manually that’s one thing.
I called them schizophrenic because the companies I’ve interviewed with seem like they desperately want to be on the AI bandwagon and want you to demonstrate the ability to effectively use AI, but they don’t currently know how to evaluate that and panic and default back to their old heuristics.
It is very difficult in 45-50 minutes to complete a task when the criteria change partway through.
I'm a consultant and I've already worked for multiple AI companies that shut down over the last two years. I think the main problem is that they all are relying on the big token providers and trying to capture value with various services.
At some point the token costs will increase so much, it will put all of these AI companies out of business.
Don't get me wrong. AI is definitely useful. The high costs are currently being subsidized by VC and other investors and unless there is a major breakthrough, it's just not going to work in the long-term.
GPT4 was more expensive than Astra. And by the time it didn't even have cache. Tokens are so cheap and so commoditized today that people already forgot how things were in the earlier days of LLMs.
Self-hosting takes either cloud- or on-prem-engineering chops, which are in short supply. In my view, that becomes the primary driver for lowering token costs. Secondary are the alternative model sources like Z.ai and Moonshot, which between open weights and lower prices help to drive commoditization. But there is a political risk with these, for example, Z.al is on the U.S. Department of Commerce Entity List, which blocks American companies from selling advanced technology and goods to the firm.
Sure but if the customer installs the app on their own computer how do companies charge them a recurring subscription fee? Adobe can get away with it but most cannot.
you seem to be discounting or unaware of the possibility of a) automating a significant chunk of new buildouts, and b) domestic companies seeking a slice of the “sell open model hosting for less than competitors” pie.
I truly believe the cost per token for most people will eventually go approximately to zero even in the absence of subsidy unless there is a dramatic state intervention to curtail free computing and hardware R&D and manufacturing.
Fair callout. Strongly discounting (b) and (a) is underspecified for me to respond reasonably.
Your premise of full token commoditization has a major wrinkle though. GPU-centric data centers with never allow tokens to go to zero since you have a 1.5 year technical deprecation and 5 year life on the GPUs. Maybe Cerebras or similar chip builders, after writing model weights to silicon, will improve those returns on capital and enabling the scaling you are envisioning.
From my perch, AI at the edge is severely underserved, and the GTM for the hyperscalers mostly ignore it. So if someone figures out how to scale AI at the edge (nvidia + HF perhaps) then I think your premise is on point.
That would be even worse for them, since then current customers of these AI-middleman corpos would just start deploying their own self-hosted and private LLM services. In before the complexity argument, there may well be some completely different middlemen corpos, who will assist in such deployments and initial ramp-ups.
Because that's been the playbook of every tech company for a decade or two. It should be our expectation that this stuff will get an expensive rug pull the instant the companies can get away with it.
People in this thread are discussing it as if it is a question of pure economics. It's not! It's a question of "how much do we think we can get away with charging"
There seems to be a weird self-fulfilling narrative here:
1) "AI companies will go bust because tokens will cost too much" >> 2) "Don't let them build data centers that will sit empty" >> 3) Demand outstrips supply by a lot >> 4) Token costs too much.
This is no different from the NIMBY's that block all the housing then sit in a huff saying "see! everyone's leaving. good thing we didn't build anything!" when the rents go up.
Talk about a goomba fallacy. The people who are against the data center buildups (which is increasingly becoming a bipartisan issue the world over thanks to the antics of the AI psychos) are not the same people complaining about token prices. I'm sure many of them would even be gleeful if the AI companies went belly up
Doesn't matter if they're different people or if it's politically popular.
It's how the cycle would go, and in the end the same people will complain about how AI "is only for rich people" (how high token prices will express itself in populist language)
Again, the people who are anti-AI don't give a shit about token prices. They will care that AI is only for rich people, but this won't be due to token prices, but because only the wealthy will be the ones with any kind of job (if the dream of the AI overlords is to come to fruition anyways) or income stream due to displacement caused by AI
I don't care what their dream is, I care about what's happening IRL. Please read the original article again, AI is clearly being used by workers to expand their productivity (and their earning capacity). The main thing that will screw that up is if token prices spike.
"AI is only for rich people, but this won't be due to token prices"
Statement doesn't make sense. Higher prices means unaffordability. I don't know why that would change for AI tokens. Higher token prices is what will make sure advanced models are only available to capital owners
This feels "unintuitive" only because it's not the dominant narrative, but that's not a measure of accuracy. "Everybody believe so" is not a good defense.
Are you seeing companies that are in over their heads because they don't have enough domain knowledge?
I think that's always been an issue in tech, but it feels like AI exacerbates the issue. I see people starting companies and services where their primary domain knowledge seems to be whatever their AI tells them. It's sometimes enough to get off the ground, but I wonder how long it takes for customers/clients who actually need the domain knowledge to bail.
I'm seeing it at small scale around me. I view it as a Dunning Kruger enablement - AI gives confident answers and long-winded explanations on domains distinct from the person asking, making it hard to verify. The user of AI now feel they have replaced someone's advice. I see it in Technology at work (particularly in architecture) but also in non work things like plumbing, law, medicine. We're all doctors and physical therapists now, for example. Also we don't need psychologists, either.
Everyone is obsolete. Just upload the MRI report to Claude and let it tell you what you should do.
When people talked about AI being a catastrophe to befall us, I thought people were picturing killer robots. What's happening instead is something else - the enablement of stupidity.
Not to mention if you make a successful value add the token provider will add it to their own harness and they're not paying the retail price they charge you for the tokens they consume.
yea this is something I've been wondering about. I'm not too keen on the finance aspect, but I understand that the big players aren't turning a profit. OpenAI is still losing money. I've seen some discussion related to increased token costs. If that continues, isn't dependence on their services a risk?
I believe this to be completely mistaken, because the bang-for-buck is getting better. Luna on max thinking is very capable and builds you a feature for 20 cents.
Its just that in a gold rush, there are few winners and many losers. There used to be hundreds of car companies in the beginning, only a dozen or so survived long term.
Most people and firms by extension don't actually A) know what people want B) re-design their operations for the technology to amplify productivity that translates into finished goods and thereby the financials and market-share.
> The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023, and appears more than enough to offset weaker hiring in many back-office roles. America’s AI infrastructure splurge has created many of them. (...) That building spree requires armies of workers: electricians to wire them, HVAC specialists to stop racks from overheating, grid engineers to hook them up to the power supply and technicians to install and maintain the machines.
I'm not sure whether the salaries of the new jobs are on par with those of the lost jobs.
"easily exceeds the roughly 200,000 lay-offs attributed to AI "
Except that is hogwash, "attributed to AI" is basically the CEO screwing up something in the business and AI-washing their mistake because it's convenient.
“One million high-paying upper-middle class family supporting jobs were destroyed, but on the bright side, one million minimum-wage Walmart greeter jobs were created! See? We’re breaking even!”
Building and maintaining data centers aren’t minimum wage jobs. They are the best kind of jobs: accessible to somewhat above average people across a broad range of backgrounds. (As opposed to upper middle class knowledge worker jobs that are only accessible to the cognitive top 10%.)
I understand building data centers, but what does maintaining data centers entail? Are those going to be high paying jobs and how many of them. I don’t know much about the area but it seems like they would be low wage and not very many needed once the data centers are built.
I think we are kidding ourselves if we think writing software was only accessible to the cognitive top 10%. And even if that were the case for the highly paid software jobs, there was a long tail of WordPress customization type jobs that required less experience and will probably be going away.
But what happens when the exec level managers are done with all these AI training sessions and rollouts and realize nothing has improved?
What about the loss of productivity of developers who are forced to entertain tons of noise about AI and take training and attend sessions which do not increase their productivity and instead takes time away from real work?
Are employers running a software shop or a church?
What happened when they all pushed cryptocurrency and nothing actually came for it? Nothing. They just stop talking about it, quietly shutdown their revolutionary services.
What happened when they all pushed for metaverse things? Nothing. Shutdown quietly, move to the next big trend you’re not allowed to ignore.
That’s it. That’s the pattern. Here some companies will get a bit of value, most won’t. Though the job of software engineer has been transformed that’s the main real impact. But companies who didn’t get much value from all their AI projects will shut them down quietly, and LLMs will just became another tool in the standard company toolbox. Until a new trend comes along
AI is a religion that promises CEOs, VCs and other various assorted sociopaths the promised land of not having to pay for the most expensive part of any business, its workers. They will do anything and everything in their power to reach this promised land, regardless of the cost to themselves, to their businesses or to society at large.
It is entirely irrelevant to them how useful LLM tech is. It doesn't matter that productivity is the same as it ever was just with a 10-fold increase in costs due to token-maxxing behaviour. They don't care if their software is buggier than ever, or their workers unhappier than ever, because AI promises to replace them anyways
I can’t read the article but in my group, which is not terribly AI exposed due to its hands-on nature, we are in fact hiring extra people into next year to handle additional AI initiatives that I am confident will succeed. In subsequent years, the plan as I have heard it is to let headcount go down by attrition.
I would not take extra hiring now as evidence that AI is preserving job numbers.
The article mostly cites the huge growth in blue-collar jobs caused by the data center buildout. It’s very handy-wavy about white collar jobs, “yes lots of jobs have been lost, but also the tech sector always has a lot of year-to-year churn, maybe this is just churn”.
Not a super insightful article. The AI jobs apocalypse may or may not be real, but this article doesn’t provide any compelling evidence for its thesis.
It's handy-wavy because nobody knows how it will turn out and which new jobs will be created. In the same way as every predictions about AI bust, job lost, moat (or lack of it) is. If you feel confident about your predictions, don't.
This is indeed HN, so comments are of course skewed to a particular upper echelon of knowledge work, but I'll ask anyways:
When you say (and perhaps you might speculate across other businesses) "hiring extra people... To handle AI initiatives" does that mean you're hiring Very niche and specialized AI people to handle these initiatives? I'm curious because I have seen some versions of this sentiment on HN and it sort of feels like reading "at my company we're hiring more quantum physicists because of these initiatives".
Basically, how much of the general populace is actually going to have a shot at nabbing a slice of this meager pie?
No we are not hiring AI experts, just people we think can be trained to think AI-natively. It’s a different mindset that presumes whatever work you’re doing now is ultimately going to be used to train AI to do it later.
ok well I went from not knowing what a tensor was to having my pi coding agent polish up my orchestration layer in about ~60 days, wheres the ai dreg hiring at?
If most of the jobs its creating are related to construction of infrastructure then that's not really positive news as these jobs are temporary, once demand settles then why kind of jobs are going to be created?
It might be benefiting other areas, but I think as the technology improves a lot of those are going to start looking like what's happening in software development (which is arguably what the technology is best at right now).
People say this all the time and it's a huge issue. A main driver of current housing issues is that no one wants to over scale and have too many temporary jobs that disappear if housing demand slows down.
Datacenter construction jobs though are very very temporary and not really the kind of thing where we can keep building for no reason and then just tear down to rebuild again.
The reason we have so many "infrastructure" bills that are basically just build more roads is that there are so many temporary road construction jobs. If they don't keep building and those workers lose their jobs it's going to be a major crisis.
"Datacenter construction jobs though are very very temporary"
They are 5-6 year long builds with full support of the unions[1], let's just put this all aside. The jobs are good. Most people citing narratives around "what's the point of doing anything if the jobs are temporary" are people who don't have those jobs.
Most of these jobs are the same jobs that arose thanks to the CHIPS and IRA. Much of the AI boom and trade is building on top of the capex that arose from the semiconductor/hardware portfolio during that era.
Many of the current DCs being built out are also being powered or tied with renewable energy projects that were funded by the IRA, as many DC builders with deep pockets do know the political dimension. If this is what keeps the CHIPS, IRA, and the IIJA alive I'm happy.
Every industry and career type goes through ebbs and flows. The 2010s was a white collar boom, and the 2020s is now a white collar bust. Meanwhile the 2010s was a skilled trades bust and the 2020s is now a skilled trades boom.
There is almost always a next big thing. What happens when it ends is people move to the next thing. Practically everything needs some kind of construction, management, software, hardware, etc.
I'd be rich if I knew what the next big thing was but the economy has been running on the assumption that there will be a next big thing for many, many decades. Each cycle has the same rhymes of "what happens when it ends" questions but there has always something.
I worked in a country for 10+ years where the economy was not that good. The only place with true guaranteed continuous employment are government services or adjacents. Anywhere else you would see layoffs, closures or salary stagnation.
The construction jobs are only temporary if the compute infrastructure build-out decelerates. That seems pretty unlikely in the mid-term! It would mean that, like, there's a fixed appetite for data centers, and once we satisfy that appetite, we stop building them.
For better or worse, it looks more like that we're gonna tile the whole damn planet in data centers, at a faster and faster clip.
While I'm still catastrophically worried about what AI means for my career, I've noticed that my current employer - very AI forward, and growing the team - is still facing an ever expanding backlog.
High productivity is generally good for the employee, unless you're productive enough you run out of work to do. So how much code is needed?
Yes I’ve seen very little change over the past 3 years in my role (platform engineering) except mostly JIRA tickets are more unreadable because people just have Claude vomit a novel into it.
I mean I use it every day of course, but the velocity of work doesn’t really seem to be budging lol. And frankly a lot of time wasted on AI made gadgets, and meetings about those gadgets (look at this dashboard Claude made! etc)
Short version is that what you, I, and other responses to you are seeing is backed up by the numbers: AI code generation leads to significant bottlenecks, burnout, increased bugs, insane code churn (rewrites), and decreased feature deployment (presumably due to dealing with the bugs and bottlenecks). And as of when this was done, increased AI did not improve the situation, it generally made it worse.
The code churn stat is what bothers me the most: People keep portraying the whole "quickly rewrite/re-generate code with AI" thing as a feature, but looking at it over time, it actually means you lose your battle-tested code and no longer have a stable foundation to build on top of. That's where I think the major problems will show up as code needs to be maintained - and, seemingly, already has been.
So much of this yes, colleagues who think doing AI work is asking Claude to, as you so eloquently wrote "vomit a novel", and allow themselves to disengage their brains.
The joke is at the level of developers, the constant sharpening of AI merge-requests reviewing (sometimes too much) has made the new job of AI speedriding & reviewsfighting a serious brain squeeze.
The value of conscienciousness has skyrocketed, and the value of openness is still the same as it ever was.
Also, anyone can take a frontier model, point it at your AI startup website/app, and replicate what makes it unique in a fraction of the time it has taken the original implementers. There is nothing magical about most companies, you cannot replicate Apple but any SaaS can be cloned quite well with a bit of time. Unless you have a really unique niche with high entry cost, or a really unique dataset, or something else that really differentiate you from all the competitors, you will find that your space gets crowded very quickly
We didn’t need to see resignations because they were fired when the numbers weren’t good, in his opinion, previously.[1]
I get that the king does multiple things per day that used to be admin ending but we shouldn’t forget his machinations that are related to the topic at hand.
The data probably isn’t 100% false but it also definitely as trustworthy as it was a year and a half ago.
> We didn’t need to see resignations because they were fired when the numbers weren’t good, in his opinion, previously.[1]
I mean no disrespect, but I have been following this story, as I am very interested in the quality of official statistics.
He did fire the BLS head, then tried to appoint a toady, but basically the big IB and investors threw a fit (along with some Senators) and it didn't happen.
So I regard most of the weirdness in these numbers since Covid as an artifact of the seasonality models breaking down, rather than some nefarious actions.
I'm very senior and in a HCOL, relatively booming city. It's never been so hard to find a job despite never being so qualified. I can code, run infra, scale startups, do hands on, manage, present, I can do anything. But that's not what they are looking for. Dozens and dozens of my applications are rejected, with no first screens.
The same resume, just with a few less years experience at the same place, just a few years ago got recruiter pings.
It's insane and I'm very worried about the future of our jobs. I also don't think AI is legitimately replacing people, as at work people are producing terrible slop and having my team review it. That's not less work, that's more work.
I hope this results in a rebalancing of the social and economic power of high-IQ versus average-IQ workers. We will need construction workers and tradespeople to build and maintain these AI data centers. Probably even with robots. But we won’t need as many engineers, lawyers, and other people whose job it is to consume and generate bits. If we tax the proceeds of AI generated productivity sufficiently, this could be the beginning of returning to the dynamics of the 1940s-1960s, where economic power was more concentrated among skilled blue collar workers than it is now.
Are you serious about this imbalance? it's the seriously rich that have taken all of the spoils, that's where the massive imbalance is.
I'm not disagreeing that some manual work require forms of intelligence that are undervalued in our society, and don't get me started about nurses, but still: What the Jeff Bezos!
> it's the seriously rich that have taken all of the spoils, that's where the massive imbalance is.
It depends on how you define “spoils.” People define it to include notional paper wealth, and I think that doesn’t reflect the actual mechanics of economic imbalance. On paper, NVIDIA’s shareholders have increased their wealth by $4.8 trillion in five years, enough to buy all the residential real estate in New York City and LA combined. But $5 trillion in notional AI wealth isn’t actually the same as owning NYC and LA. The paper wealth doesn’t affect the average person meaningfully until someone actually buys something with it.
Given that, it’s more useful to define “spoils” in terms of finite goods and services and look at spending on those goods and services. That is what directly affects the average person—it’s what makes housing or education or Disney tickets or whatever harder to access.
And on that front, the income growth of the top 10% has had a much more significant impact on the average person. The top 10% accounts for half of consumer spending today, up from 35% in the 1990s. And that spending is coming from the upper middle class, not billionaires. Bezos might be worth a million times more than the average person, but he’s not buying a million times more housing or Disney tickets or hotel rooms. Instead, the average person is competing directly with the increasingly affluent top 10% for access to those finite resources.
The bigger issue is weak competition. When a few companies dominate a market, they can raise prices, suppress wages, and capture more of the gains from economic growth.
That is also a big part of why wealth has become so concentrated at the top. If there were ten real cloud competitors, eight GPU makers, or several serious Office competitors, those companies would have a much harder time keeping such a large share of the profit. Instead, concentrated markets create enormous profits, and concentrated ownership turns those profits into enormous fortunes.
In my opinion, that has a bigger impact on the bottom 90%, and even on the upper middle 10% you are talking about, than the direct consumption of the top 10% ever could. It would be much better to raise the purchasing power of the bottom 90% than to reduce the consumption of the top 10%.
This is really a point that I think goes so misunderstood by so many. Yes billionaire's are bad, but people making 3x the median have a much bigger impact on those making median or less.
I think it’s possible AI job disruption (or the threat thereof) could lead to a new labor movement capable of uniting people across the isle. It remains to be seen, but I think if the threat of a “permanent underclass” isn’t enough to get people to compromise and cooperate, nothing will.
People need to update their priors. The “permanent underclass” concern arose from a time when people thought AI was going to dominated by the first company to achieve it. But now we see that AI is becoming commoditized faster than almost any technology in recent history. IBM and Microsoft had a monopoly on personal computing for decades. AI is becoming a commodity before any of the AI companies have even turned a profit.
AI is going to be like electric motors. If you had a monopoly on electric motors you could control the world! But instead they’re commodity products mass manufactured around the world
I think this is Jevon's paradox playing out in full force, and I'm quite confident we'll continue to see the growth in well paid STEM jobs despite the anecdata in this thread (anecdotally my group of ICs on tech have all seen our comp grow a lot in the last few years)
Until we saturate the demand for software which may very well be infinite
The jobs numbers have been terrible and revised down. Huge amounts of people have dropped out if the workforce or are employed in multiple part times or struggling seriously in a single full time.
I saw an article here about the job market for writers. I can't recall, but I think it was a blog post saying like "AI is bad and has annoying prose so GOOD writers will thrive". The comments rightfully pointed out that not everything requires good writing and many companies will "buy" writing for llm prices as good enough to save money.
I bring it up because that is where someone simply articulated the obvious point I hadn't really thought through: the cascade. What happens when millions of copywriters, non famous journalist, average graphic designers, etc. get laid off. Millions of people will drive the price of labor WAY down as this wage bubble wanders through industries popping every few months. If the supply if labor becomes massive, we will have this debt spiral or stagflationary labor market that causes chaos. Ultimately, capital owners accrue the most value and can buy tons of assets for cheap. Unless, it turns out a middle classes consumption is like...important for our country to function.
As a programmer, but working in two non-SWE roles, I have turned job A 70% over to AI, and job B 90%.
Where systems and scaffolds can be put in place to manage various aspects of a job, would this not be considered, partially, an "AI job"?
If you work in government grants and R&D, what if agents can now triage 100-1000x the opportunity count that you could ever handle alone, and you had a pipeline system in place to manage said opportunities and relationships? And then you, as the human, become the mouthpiece and reviewer of hoards of filtered output? Is that Federal Grants & R&D position now not mostly an AI job?
I'd say a large percentage of digital-based jobs can be considered varying percentages of AI jobs.
I think they mean jobs directly related to AI, not merely exercising AI to increase productivity:
AI is also creating a new class of white-collar jobs. Engineers build the models, data annotators label their inputs and judge their answers, “forward-deployed” engineers adapt them for customers, and newly minted “heads of AI” decide what companies should do with the technology.
AI boosters: "look, AI is creating jobs, all of these doomers scaring you with job loses, don't listen to them"
also AI boosters: "we are going to build a million robots, and the robots will build factories producing robots, there will be infinite abundance, nobody will need to work anymore"
When AI gets that good, a solar panel can power a pile of motors and gears to move and do work for you that previously required humans. You won't need the job, you need to solve your necessities more directly. And that job is a good fit for the AI that was so good it put you out of a job.
> On September 4th the Bureau of Labour Statistics reported that the American economy added 162,000 jobs in August, far above expectations.
Good news that ought to be taken with a pinch of salt given how the current administration responds to unfavorable BLS data -
> On Friday, August 1, [2025] President Trump fired Dr. Erika McEntarfer from her role as the Commissioner of the Bureau of Labor Statistics (BLS). In social media posts announcing and confirming her firing, he said that he believed the jobs report released by the agency earlier that day included numbers that were “rigged in order to make the Republicans, and ME, look bad.”
The first series of "Blackadder" has a vignette of such reportage:
Messenger 3: My Lord, news…
King: What?
Messenger 3: Lord Wessex is dead.
King: This news is not so good.
Messenger 3: Pardon, My Lord?
King: I like it not. Bring me some other news.
Messenger 3: Pardon, My Lord?
King: I LIKE NOT THIS NEWS! BRING ME SOME OTHER NEWS!!!
Messenger 3: Yes, My Lord!
(Messenger 3 leaves; King tosses things around angrily;
Messenger 4 enters — actually just Messenger 3 pretending to be a new messenger delivering new news.)
Messenger 4: My Lord, news…
King: What?
Messenger 4: Lord Wessex is not dead.
King: Ah, good news! Let there be joy and celebration; let jubilation reign!
Even outside of the current administration, isn't BLS data notorious for being adjusted after the fact, often downwards? Basing reporting on fresh BLS data seems ill-advised.
Wasn’t she only in that job for a year? Maybe she was doing a bad job.
The current head of the BLS seems well qualified. Here are some select quotes from a NYT article [1]:
“Erica Groshen, who was commissioner during the Obama administration, also praised the selection. “He’s a B.L.S.-er, he’s a data nerd,” she said.”
“The firing, and Mr. Antoni’s subsequent nomination, raised concerns that Mr. Trump would seek to interfere in the agency’s operations and perhaps try to skew its estimates to his political advantage. “
“There is no evidence that has happened so far. The agency has been run since August by William Wiatrowski, its longtime deputy commissioner, who also led the bureau on an interim basis under President Joseph R. Biden Jr. Economists continue to view the numbers the agency produces as reliable.”
Now these comments were written back in January of this year.
Can you cite any specific examples of wrongdoing? Or inaccurate numbers or figures outside of normal revisions?
When I see bad numbers from the BLS I say yes that’s probably true. When I see good numbers from the BLS I say yes that’s probably true.
I've spent 10 years implementing new technology into businesses from all over the world and the thing that has killed the most projects at the proof of concept phase has not been whether it works. It's whether the cost of going to production from PoC produces a significant ROI. AI is absolutely changing the economics there.
Humans were simply nowhere near answering all the useful questions they had which software could answer. The problem was that software was expensive.
Now, software is cheaper and so people who couldn't afford to answer questions they've long wondered about can afford to answer them.
>people who couldn't afford to answer questions they've long wondered about can afford to answer them.
If the software isn't downright free – today, you can slap a $349 RTX 5060 [†] into any POS surplus computer and have an offline assistant, running Llama or Ornith, via Ollama in linux (i.e. the LLM and OS are FREE open-source software) [∑]
I have a working demo of this that has been shown/leant to several friends, and they're all surprised that it "all works so well, without being online, for only a few hundred dollars."
When I've demonstrated Mistral-small on my 5070Ti... that has been a real jaw dropper. I haven't shown anybody qwen3.8:27b, yet... but dammmmm, what a month of learning it's been.
----
A friend that was going through wifecancer confided in me that "you can ask it anything, without feeling embarassed" – and that has stuck with me (that so many smart people are afraid to ask simple questions [*], out of perceptional worries).
----
[†] (8GB DDR7) brand new from Wal-Mart
[∑] My first linux/LLM machine was built with setup help from Perplexity.ai (with a dozen "assists" - I am bluecollar, non-coder). This used an obsolete i5 (and $200 used VEGA64 GPU) to create a decent Llama3.1 LLM machine (~100wpm typeback, perhaps 70 tokens/s).
[*] even to their own detriment, of shame, when simple solutions often do exist
No longer convinced that’s true. Some of the indebted providers might go under but there is nothing preventing someone from just setting up a new provider and serving tokens debt free. GLM or whatever.
That provides continuous downward pressure on token prices even if it isn’t Astra level
Agree model providers can't take much margin, a few percent plus maybe a bit extra from those willing to pay for a "better" model. Upstream is more concentrated: TSMC, NVIDIA, AMD could maybe raise prices and capture more of the value, which would affect open model providers.
Do you have any evidence to suggest that this true? And if so, why can't I just use any of the very good open source Chinese models (and eventually American once reflection, thinking machines, etc catch up).
I haven't had a job in 4 years. Well okay I am an old piece of shit of 49 yrs old with a Stanford degree. So obsolete for this new AI world of imaginary bullshits. So I deserve it
>The Economist, Silicon Valley's primary submarine, dispels the notion that AI causes unemployment because SV has realized that the peasants get unruly.
Right, but OP's implication is that they're trying to placate the masses (that somehow read the economist?), even though a few months before they were putting out alarmist covers. You can't have it both ways. If you're arguing that economist being pro-job loss is part of a globalist conspiracy and so is the economist being anti-job loss, then you just created an unfalsifiable statement, a "heads I win, tails you lose" argument.
I was laid off as a senior product manager in December of 2025. I’ve been looking for a new job in clean energy (which is supposedly “having a moment” due to data centers) since then. There is no “jobs boom”. There are certainly job openings — black holes into which you can lodge your resume. Occasionally, multiple rounds of interviews that go nowhere. I’ve been paying my bills as an art fabricator and live event electrician, the kinds of blue collar jobs that are supposed to make up for the destruction of “knowledge work”. The work is inconsistent, and the pay is less than half of what I made before. There is no “jobs boom”, of any kind.
I don't think this is entirely true: let's just say the jobs boom is unevenly distributed. There are definitely more openings than there were a year ago, but it is also now much more of a challenge to effectively market yourself as a person in tech.
On the one hand there is the problem that every job posting is flooded with hundreds of bogus AI resumes which, if they are not outright fabrications, stretch the truth enough to make it hard to tell who is qualified and who is not.
Anecdotally, it seems to me like directly applying to jobs is a waste. You either have to find some way to attract recruiter outreach, or network with people who can get you a foot in the door.
There are no job openings. The ones you see are fake.
I've applied to the same FAANG opening in Sydney 3x over the last 1.5 years. It's not a real job as apparently they're not eager to fill it for years.
> There are certainly job openings — black holes into which you can lodge your resume
And recruiters are just flat out creating fake job listings on Indeed, with no pretense, describing them as "an opportunity to register your interest in similar roles", and Indeed are allowing it.
No they are not, try to change jobs and if you can't or takes a really long time you know this is some of the finest baloney. And no, it's not creating a lot of jobs, one one of the kind that will be destroyed by AI no, and that's the point... you built something that removes the pricey laywer, software developer, insurance policy writer, designer, etc... and replace it with a ONE TIME go work under the sun with no ac in the middle of nowhere as a contractor of the contractor of the contractor... So sure, I'm a dooms-scroll-lover, sure the 10000000 new part time possitions with no benefit of any kind will be the biggest work boom EVER... you will just go to compete with all the other people already doing that... and you know what happens when there is a queue of 100 to flip burgers or "highly technical non AI replaceable work like weld or electricist" right??
"you built something that removes the pricey laywer, software developer, insurance policy writer, designer"
This statement is untrue. The people have the judgement, the AI does the rote work. The rest is marketing fluff and/or leadership fumbles. You can't get rid of judgement (unless of course leadership is fumbling).
With more AI, you got more radiology requests, and more radiologists [1] and better health results due to more abundant measurement. There is no evidence that the same isn't happening to the rest of the professions. And to support it all, we have more infrastructure construction (datacenters).
This is the textbook basics of a growing economy with growing productivity, even though it feels paradoxical [2]
[1]: https://www.ft.com/content/f2e03bd9-af67-45c4-8e1e-79978b5bc...
[2]: https://en.wikipedia.org/wiki/Jevons_paradox
Jevons Paradox doesn't say more radiologist will have more work and will be paid at the same price, it says that there will be more work for radiologists because now they are paid less and because of that people is able to afford more radiologists.
"This statement is untrue. The people have the judgement, the AI does the rote work. The rest is marketing fluff and/or leadership fumbles. You can't get rid of judgement (unless of course leadership is fumbling)."
Let me refine it more... now the same lawyer/marketing/software engineer can work just approving the work of AI, reviewing it's correct so the exact same lawyer/marketing/software engineer can now perform X more times the amount of work they previously did, IF we don't triple the amount of work, then the rules of "free market" means that offer now exceeds by X the demand and you can now depress wages as much as you want because you can fire (x-1)/x of the people doing the work and the pool of people willing or needing to do that is increased.
This does not contradict at all what I stated above.
The ultimate proof of this is how much the "calculator people" now earns now that calculators were created... and for reference this old ad about the effect of calculators on the number of engineers
[0]: https://www.globalnerdy.com/wordpress/wp-content/uploads/200...
"radiologists because now they are paid less and because of that people is able to afford more radiologists."
But again, the opposite is happening. Radiologist salaries are up 9% YoY [1]. And you can now get your radiology done more cheaply [2]. Literal win-win.
Radiologists are not human calculators, neither are lawyers, accountants or insurance adjusters. As we learned very quickly, their job is judgement and human relationships and you can't cut that out
You did correctly lay out that if you can't grow your business by increasing demand, you are shrinking. And yes shrinking leads to layoffs regardless of AI.
Very cliched now but: You are not being replaced by AI, you are being replaced by someone who's using AI, who is more productive with it. But specifically, this is true for individuals and company-wide. Less productive organizations will be pushed out if they can't lower their prices and meet the increasing demand, and the only way they do that for modern white-collar work (not rote 1950's calculator churning) is to hire more AI-ready staff.
FWIW, The IBM ad is literal marketing fluff. More engineers were employed in the immediate aftermath of the mainframe than anytime before.
EDIT: I'm not trying to argue with you, I'm trying to show you things most headline news refuses to show because it's boring and counter-narrative. Shoutout to the economist.
[1]: https://fortune.com/article/ai-godfather-radiologists-obsole...
[2]: https://pmc.ncbi.nlm.nih.gov/articles/PMC10986240/
Exactly spot on.
Why are people so stupid?
E.g. take the radiology example. In the past people would not have been sent to a radiologist due to resource constraints.
But because of AI you now more capacity - therefore there is an INCREASE in radiology requests.
And this is going to be the common theme - there are lots of things that people are doing right now has an implicit constraint. AI will unlock new capacity so we will see MORE of it -> this will actually create a bizarre scenario of a labour shortage in many respects.
I know that's not what Amodei and Altman want to hear but... ha.
THis is why people are so bad at predictions - they look at one variable move and forget the rest / many 'unknowns' they did not foresee.
if you're going by anecdata, myself and a few of my colleagues (senior ics) switched jobs relatively easily for a solid pay increase within the last year. definitely easier than post-covid
engineering (hardware, software) and data center construction are going through a boom cycle right now and will eventually bust, and so on and so forth
And the robots are just a few years away. I thought that spatial reasoning was going to be a lot harder for AI, but Astra is showing that progress on that front is also moving very rapidly.
humanoid robots are decades away, and they are not going to be good or cheap for a long time.
> humanoid robots are decades away
I think the world has gone too crazy to make any such claim. They could be decades away, they could be a year away.
Remember that it doesn't have to be necessarily better than a human, it just needs to make economical sense. A robot that fails 20% of the time but costs 0.10$/h to run beats a person for many tasks.
Decades? Or less than a decade?
Less than a decade with 99.999% certainty.
"humanoid" robots are as relevant to commercial robotics as AGI to LLM, that is, not at all. As long as they can move on wheels and operate 2 hands (doesn't matter how many fingers), the application is huge already.
AI has completely broken interviewing as well. The asks I am getting in the few interviews I can achieve are schizophrenic.
They have pretty uniformly wanted me to demonstrate using AI but then freak out and interrogate me for every prompt and then want me to demonstrate I can do the task by hand. And that’s only after getting through the AI run filtering that gives a different score everytime your unchanged resume is run through the model.
It’s dark times for employment currently unless you’ve got a rare nepotism path.
It was always better to find job via recommendations. Both for companies and candidates. Old leetcode style interviews were no better at identifying good candidates for given job.
> It’s dark times for employment currently unless you’ve got a rare nepotism path.
In the civilized society, we call that "recommendation".
I don’t know if those companies are doing it for the right reasons but I’ve implemented a policy of showing me that you can do the job manually as well.
The reason being that if you can’t then you probably can’t tell when the AI is wrong.
My company is strictly Cybersecurity/IR though so that may vary with other specialties.
If the interview was specifically about doing it manually that’s one thing.
I called them schizophrenic because the companies I’ve interviewed with seem like they desperately want to be on the AI bandwagon and want you to demonstrate the ability to effectively use AI, but they don’t currently know how to evaluate that and panic and default back to their old heuristics.
It is very difficult in 45-50 minutes to complete a task when the criteria change partway through.
Oh yeah no that’s just a terrible interview process.
I think schizophrenic is a great way to describe that.
I'm a consultant and I've already worked for multiple AI companies that shut down over the last two years. I think the main problem is that they all are relying on the big token providers and trying to capture value with various services.
At some point the token costs will increase so much, it will put all of these AI companies out of business.
Don't get me wrong. AI is definitely useful. The high costs are currently being subsidized by VC and other investors and unless there is a major breakthrough, it's just not going to work in the long-term.
GPT4 was more expensive than Astra. And by the time it didn't even have cache. Tokens are so cheap and so commoditized today that people already forgot how things were in the earlier days of LLMs.
Why assume token costs will increase as opposed to become commoditized?
Self-hosting takes either cloud- or on-prem-engineering chops, which are in short supply. In my view, that becomes the primary driver for lowering token costs. Secondary are the alternative model sources like Z.ai and Moonshot, which between open weights and lower prices help to drive commoditization. But there is a political risk with these, for example, Z.al is on the U.S. Department of Commerce Entity List, which blocks American companies from selling advanced technology and goods to the firm.
On macs you just install a desktop app. What can be simpler? Decent Qwen models already doing some simpler types of agentic work.
Sure but if the customer installs the app on their own computer how do companies charge them a recurring subscription fee? Adobe can get away with it but most cannot.
you seem to be discounting or unaware of the possibility of a) automating a significant chunk of new buildouts, and b) domestic companies seeking a slice of the “sell open model hosting for less than competitors” pie.
I truly believe the cost per token for most people will eventually go approximately to zero even in the absence of subsidy unless there is a dramatic state intervention to curtail free computing and hardware R&D and manufacturing.
Fair callout. Strongly discounting (b) and (a) is underspecified for me to respond reasonably.
Your premise of full token commoditization has a major wrinkle though. GPU-centric data centers with never allow tokens to go to zero since you have a 1.5 year technical deprecation and 5 year life on the GPUs. Maybe Cerebras or similar chip builders, after writing model weights to silicon, will improve those returns on capital and enabling the scaling you are envisioning.
From my perch, AI at the edge is severely underserved, and the GTM for the hyperscalers mostly ignore it. So if someone figures out how to scale AI at the edge (nvidia + HF perhaps) then I think your premise is on point.
Maybe they still want to serve the feee tokens if that gets them good training data.
That would be even worse for them, since then current customers of these AI-middleman corpos would just start deploying their own self-hosted and private LLM services. In before the complexity argument, there may well be some completely different middlemen corpos, who will assist in such deployments and initial ramp-ups.
Right now they're losing billions/year, it's not sustainable
Because that's been the playbook of every tech company for a decade or two. It should be our expectation that this stuff will get an expensive rug pull the instant the companies can get away with it.
> the instant the companies can get away with it
LLMs have no lock in. Switching costs are zero. It's really not clear that instant will ever come
Yes, this exactly.
People in this thread are discussing it as if it is a question of pure economics. It's not! It's a question of "how much do we think we can get away with charging"
There seems to be a weird self-fulfilling narrative here:
1) "AI companies will go bust because tokens will cost too much" >> 2) "Don't let them build data centers that will sit empty" >> 3) Demand outstrips supply by a lot >> 4) Token costs too much.
This is no different from the NIMBY's that block all the housing then sit in a huff saying "see! everyone's leaving. good thing we didn't build anything!" when the rents go up.
Talk about a goomba fallacy. The people who are against the data center buildups (which is increasingly becoming a bipartisan issue the world over thanks to the antics of the AI psychos) are not the same people complaining about token prices. I'm sure many of them would even be gleeful if the AI companies went belly up
Doesn't matter if they're different people or if it's politically popular.
It's how the cycle would go, and in the end the same people will complain about how AI "is only for rich people" (how high token prices will express itself in populist language)
The exact thing happened to housing.
Again, the people who are anti-AI don't give a shit about token prices. They will care that AI is only for rich people, but this won't be due to token prices, but because only the wealthy will be the ones with any kind of job (if the dream of the AI overlords is to come to fruition anyways) or income stream due to displacement caused by AI
"dream of the AI overlords"
I don't care what their dream is, I care about what's happening IRL. Please read the original article again, AI is clearly being used by workers to expand their productivity (and their earning capacity). The main thing that will screw that up is if token prices spike.
"AI is only for rich people, but this won't be due to token prices"
Statement doesn't make sense. Higher prices means unaffordability. I don't know why that would change for AI tokens. Higher token prices is what will make sure advanced models are only available to capital owners
This feels "unintuitive" only because it's not the dominant narrative, but that's not a measure of accuracy. "Everybody believe so" is not a good defense.
Are you seeing companies that are in over their heads because they don't have enough domain knowledge?
I think that's always been an issue in tech, but it feels like AI exacerbates the issue. I see people starting companies and services where their primary domain knowledge seems to be whatever their AI tells them. It's sometimes enough to get off the ground, but I wonder how long it takes for customers/clients who actually need the domain knowledge to bail.
I'm seeing it at small scale around me. I view it as a Dunning Kruger enablement - AI gives confident answers and long-winded explanations on domains distinct from the person asking, making it hard to verify. The user of AI now feel they have replaced someone's advice. I see it in Technology at work (particularly in architecture) but also in non work things like plumbing, law, medicine. We're all doctors and physical therapists now, for example. Also we don't need psychologists, either.
Everyone is obsolete. Just upload the MRI report to Claude and let it tell you what you should do.
When people talked about AI being a catastrophe to befall us, I thought people were picturing killer robots. What's happening instead is something else - the enablement of stupidity.
GPT 5.6 Luna is ten times cheaper than GPT 4o and outperforms it. I genuinely don’t think Luna is more expensive to serve than GPT 4o.
If you were charging $10 per month per user for your SaaS when GPT 4o was launched, you can easily charge $5 now and increase your profit.
I’m not sure why you believe things will become more expensive.
Not to mention if you make a successful value add the token provider will add it to their own harness and they're not paying the retail price they charge you for the tokens they consume.
yea this is something I've been wondering about. I'm not too keen on the finance aspect, but I understand that the big players aren't turning a profit. OpenAI is still losing money. I've seen some discussion related to increased token costs. If that continues, isn't dependence on their services a risk?
I believe this to be completely mistaken, because the bang-for-buck is getting better. Luna on max thinking is very capable and builds you a feature for 20 cents.
Its just that in a gold rush, there are few winners and many losers. There used to be hundreds of car companies in the beginning, only a dozen or so survived long term.
ERm said another way.
Most people and firms by extension don't actually A) know what people want B) re-design their operations for the technology to amplify productivity that translates into finished goods and thereby the financials and market-share.
[dead]
> The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023, and appears more than enough to offset weaker hiring in many back-office roles. America’s AI infrastructure splurge has created many of them. (...) That building spree requires armies of workers: electricians to wire them, HVAC specialists to stop racks from overheating, grid engineers to hook them up to the power supply and technicians to install and maintain the machines.
I'm not sure whether the salaries of the new jobs are on par with those of the lost jobs.
"easily exceeds the roughly 200,000 lay-offs attributed to AI "
Except that is hogwash, "attributed to AI" is basically the CEO screwing up something in the business and AI-washing their mistake because it's convenient.
I thought the whole thing was AI was leading to underhiring not necessarily layoffs
“One million high-paying upper-middle class family supporting jobs were destroyed, but on the bright side, one million minimum-wage Walmart greeter jobs were created! See? We’re breaking even!”
Building and maintaining data centers aren’t minimum wage jobs. They are the best kind of jobs: accessible to somewhat above average people across a broad range of backgrounds. (As opposed to upper middle class knowledge worker jobs that are only accessible to the cognitive top 10%.)
I understand building data centers, but what does maintaining data centers entail? Are those going to be high paying jobs and how many of them. I don’t know much about the area but it seems like they would be low wage and not very many needed once the data centers are built.
I think we are kidding ourselves if we think writing software was only accessible to the cognitive top 10%. And even if that were the case for the highly paid software jobs, there was a long tail of WordPress customization type jobs that required less experience and will probably be going away.
yes my comment was a satire of your thinking here, not an actual representation of reality
But what happens when the exec level managers are done with all these AI training sessions and rollouts and realize nothing has improved?
What about the loss of productivity of developers who are forced to entertain tons of noise about AI and take training and attend sessions which do not increase their productivity and instead takes time away from real work?
Are employers running a software shop or a church?
What happened when they all pushed cryptocurrency and nothing actually came for it? Nothing. They just stop talking about it, quietly shutdown their revolutionary services.
What happened when they all pushed for metaverse things? Nothing. Shutdown quietly, move to the next big trend you’re not allowed to ignore.
That’s it. That’s the pattern. Here some companies will get a bit of value, most won’t. Though the job of software engineer has been transformed that’s the main real impact. But companies who didn’t get much value from all their AI projects will shut them down quietly, and LLMs will just became another tool in the standard company toolbox. Until a new trend comes along
They can't afford to miss out or be seen as missing out. It's not rational, yet it is in a way.
The Church of Chief Executives.
AI is a religion that promises CEOs, VCs and other various assorted sociopaths the promised land of not having to pay for the most expensive part of any business, its workers. They will do anything and everything in their power to reach this promised land, regardless of the cost to themselves, to their businesses or to society at large.
It is entirely irrelevant to them how useful LLM tech is. It doesn't matter that productivity is the same as it ever was just with a 10-fold increase in costs due to token-maxxing behaviour. They don't care if their software is buggier than ever, or their workers unhappier than ever, because AI promises to replace them anyways
I can’t read the article but in my group, which is not terribly AI exposed due to its hands-on nature, we are in fact hiring extra people into next year to handle additional AI initiatives that I am confident will succeed. In subsequent years, the plan as I have heard it is to let headcount go down by attrition.
I would not take extra hiring now as evidence that AI is preserving job numbers.
The article mostly cites the huge growth in blue-collar jobs caused by the data center buildout. It’s very handy-wavy about white collar jobs, “yes lots of jobs have been lost, but also the tech sector always has a lot of year-to-year churn, maybe this is just churn”.
Not a super insightful article. The AI jobs apocalypse may or may not be real, but this article doesn’t provide any compelling evidence for its thesis.
It's handy-wavy because nobody knows how it will turn out and which new jobs will be created. In the same way as every predictions about AI bust, job lost, moat (or lack of it) is. If you feel confident about your predictions, don't.
This is indeed HN, so comments are of course skewed to a particular upper echelon of knowledge work, but I'll ask anyways:
When you say (and perhaps you might speculate across other businesses) "hiring extra people... To handle AI initiatives" does that mean you're hiring Very niche and specialized AI people to handle these initiatives? I'm curious because I have seen some versions of this sentiment on HN and it sort of feels like reading "at my company we're hiring more quantum physicists because of these initiatives".
Basically, how much of the general populace is actually going to have a shot at nabbing a slice of this meager pie?
No we are not hiring AI experts, just people we think can be trained to think AI-natively. It’s a different mindset that presumes whatever work you’re doing now is ultimately going to be used to train AI to do it later.
ok well I went from not knowing what a tensor was to having my pi coding agent polish up my orchestration layer in about ~60 days, wheres the ai dreg hiring at?
Ahh I see. Any spots for philosopher / educators?
What type of activities your group performs?
If most of the jobs its creating are related to construction of infrastructure then that's not really positive news as these jobs are temporary, once demand settles then why kind of jobs are going to be created?
It might be benefiting other areas, but I think as the technology improves a lot of those are going to start looking like what's happening in software development (which is arguably what the technology is best at right now).
So yeah, idk.
AI construction jobs are temporary up to Kardashev 3 or so.
But it will be automated long before then
Humans become irrelevant well before then.
We not gonna make it to level 1, bro
Isn't this true for "all" construction? Nobody says,
"The housing construction jobs are temporary, we shouldn't count them."
There will always be CapEx to spend.
People say this all the time and it's a huge issue. A main driver of current housing issues is that no one wants to over scale and have too many temporary jobs that disappear if housing demand slows down.
Datacenter construction jobs though are very very temporary and not really the kind of thing where we can keep building for no reason and then just tear down to rebuild again.
The reason we have so many "infrastructure" bills that are basically just build more roads is that there are so many temporary road construction jobs. If they don't keep building and those workers lose their jobs it's going to be a major crisis.
"Datacenter construction jobs though are very very temporary"
They are 5-6 year long builds with full support of the unions[1], let's just put this all aside. The jobs are good. Most people citing narratives around "what's the point of doing anything if the jobs are temporary" are people who don't have those jobs.
[1]: https://futurism.com/artificial-intelligence/building-trade-...
Most of these jobs are the same jobs that arose thanks to the CHIPS and IRA. Much of the AI boom and trade is building on top of the capex that arose from the semiconductor/hardware portfolio during that era.
Many of the current DCs being built out are also being powered or tied with renewable energy projects that were funded by the IRA, as many DC builders with deep pockets do know the political dimension. If this is what keeps the CHIPS, IRA, and the IIJA alive I'm happy.
Every industry and career type goes through ebbs and flows. The 2010s was a white collar boom, and the 2020s is now a white collar bust. Meanwhile the 2010s was a skilled trades bust and the 2020s is now a skilled trades boom.
Skilled trade still isn't paying either.
There is almost always a next big thing. What happens when it ends is people move to the next thing. Practically everything needs some kind of construction, management, software, hardware, etc.
I'd be rich if I knew what the next big thing was but the economy has been running on the assumption that there will be a next big thing for many, many decades. Each cycle has the same rhymes of "what happens when it ends" questions but there has always something.
Everything is temporary, especially jobs.
insightful
I worked in a country for 10+ years where the economy was not that good. The only place with true guaranteed continuous employment are government services or adjacents. Anywhere else you would see layoffs, closures or salary stagnation.
The construction jobs are only temporary if the compute infrastructure build-out decelerates. That seems pretty unlikely in the mid-term! It would mean that, like, there's a fixed appetite for data centers, and once we satisfy that appetite, we stop building them.
For better or worse, it looks more like that we're gonna tile the whole damn planet in data centers, at a faster and faster clip.
https://archive.md/5hi5i
While I'm still catastrophically worried about what AI means for my career, I've noticed that my current employer - very AI forward, and growing the team - is still facing an ever expanding backlog.
High productivity is generally good for the employee, unless you're productive enough you run out of work to do. So how much code is needed?
I was also sure to be homeless by now. But despite aggressively trying to automate myself away I'm somehow more busy than ever.
Relatable. Every time I finish working on something, I spot so many more new things that can be built.
And because of you we are now looking bad, so you're pressuring us with your unleashed creativity.
Yes I’ve seen very little change over the past 3 years in my role (platform engineering) except mostly JIRA tickets are more unreadable because people just have Claude vomit a novel into it.
I mean I use it every day of course, but the velocity of work doesn’t really seem to be budging lol. And frankly a lot of time wasted on AI made gadgets, and meetings about those gadgets (look at this dashboard Claude made! etc)
You may be interested in this report from earlier this year: https://www.faros.ai/blog/ai-acceleration-whiplash-takeaways
And a breakdown of it that gives a bit of an alternate explanation of their numbers (and more closely matches what we're seeing IMO): https://unessays.substack.com/p/talk-is-cheap
Short version is that what you, I, and other responses to you are seeing is backed up by the numbers: AI code generation leads to significant bottlenecks, burnout, increased bugs, insane code churn (rewrites), and decreased feature deployment (presumably due to dealing with the bugs and bottlenecks). And as of when this was done, increased AI did not improve the situation, it generally made it worse.
The code churn stat is what bothers me the most: People keep portraying the whole "quickly rewrite/re-generate code with AI" thing as a feature, but looking at it over time, it actually means you lose your battle-tested code and no longer have a stable foundation to build on top of. That's where I think the major problems will show up as code needs to be maintained - and, seemingly, already has been.
It absolutely has for me. Hours/days out of a month of smashing my head against silly bugs or SQL syntax errors have gone away.
I will agree that some of the savings has been eaten up elsewhere. Lots of trivial but not wrong PR comments ther lead to churn as an example.
So much of this yes, colleagues who think doing AI work is asking Claude to, as you so eloquently wrote "vomit a novel", and allow themselves to disengage their brains.
The joke is at the level of developers, the constant sharpening of AI merge-requests reviewing (sometimes too much) has made the new job of AI speedriding & reviewsfighting a serious brain squeeze.
The value of conscienciousness has skyrocketed, and the value of openness is still the same as it ever was.
>just have Claude vomit a novel into it
True, that's the other side of it: my daily work has lost the fun reward loop and I'm being alienated from my colleagues. But I still have colleagues!
> Claude vomit
Stealing this, will use instead of AI slop!
"AI startups are hiring like there's no tomorrow."
For AI startups there eventually may be no tomorrow
How many of these startups are profitable
Perhaps the greatest "AI"-related job losses will be failed "AI" startups
More BS "jobs" created from throwaway investment capital instead of business success
Also, anyone can take a frontier model, point it at your AI startup website/app, and replicate what makes it unique in a fraction of the time it has taken the original implementers. There is nothing magical about most companies, you cannot replicate Apple but any SaaS can be cloned quite well with a bit of time. Unless you have a really unique niche with high entry cost, or a really unique dataset, or something else that really differentiate you from all the competitors, you will find that your space gets crowded very quickly
Does anyone here question the integrity of the US government’s jobs report two months away from a mid-term election?
Yes, but if you haven't been questioning them for the past couple of decades, you haven't been paying attention.
Not really. We'd see a lot of resignations if the numbers were being fudged. Statisticians, as a rule, take a dim view of falsifying data.
We didn’t need to see resignations because they were fired when the numbers weren’t good, in his opinion, previously.[1]
I get that the king does multiple things per day that used to be admin ending but we shouldn’t forget his machinations that are related to the topic at hand.
The data probably isn’t 100% false but it also definitely as trustworthy as it was a year and a half ago.
[1] https://finance.yahoo.com/economy/articles/trump-fired-bls-c...
> We didn’t need to see resignations because they were fired when the numbers weren’t good, in his opinion, previously.[1]
I mean no disrespect, but I have been following this story, as I am very interested in the quality of official statistics.
He did fire the BLS head, then tried to appoint a toady, but basically the big IB and investors threw a fit (along with some Senators) and it didn't happen.
So I regard most of the weirdness in these numbers since Covid as an artifact of the seasonality models breaking down, rather than some nefarious actions.
> AI startups are hiring like there is no tomorrow.
This is not reassuring
Yeah. It’s like well, that would be great if there was no tomorrow, but the thing about tomorrow is that it always famously comes.
I'm very senior and in a HCOL, relatively booming city. It's never been so hard to find a job despite never being so qualified. I can code, run infra, scale startups, do hands on, manage, present, I can do anything. But that's not what they are looking for. Dozens and dozens of my applications are rejected, with no first screens.
The same resume, just with a few less years experience at the same place, just a few years ago got recruiter pings.
It's insane and I'm very worried about the future of our jobs. I also don't think AI is legitimately replacing people, as at work people are producing terrible slop and having my team review it. That's not less work, that's more work.
Has Idiocracy reached our industry?
I hope this results in a rebalancing of the social and economic power of high-IQ versus average-IQ workers. We will need construction workers and tradespeople to build and maintain these AI data centers. Probably even with robots. But we won’t need as many engineers, lawyers, and other people whose job it is to consume and generate bits. If we tax the proceeds of AI generated productivity sufficiently, this could be the beginning of returning to the dynamics of the 1940s-1960s, where economic power was more concentrated among skilled blue collar workers than it is now.
Are you serious about this imbalance? it's the seriously rich that have taken all of the spoils, that's where the massive imbalance is.
I'm not disagreeing that some manual work require forms of intelligence that are undervalued in our society, and don't get me started about nurses, but still: What the Jeff Bezos!
> it's the seriously rich that have taken all of the spoils, that's where the massive imbalance is.
It depends on how you define “spoils.” People define it to include notional paper wealth, and I think that doesn’t reflect the actual mechanics of economic imbalance. On paper, NVIDIA’s shareholders have increased their wealth by $4.8 trillion in five years, enough to buy all the residential real estate in New York City and LA combined. But $5 trillion in notional AI wealth isn’t actually the same as owning NYC and LA. The paper wealth doesn’t affect the average person meaningfully until someone actually buys something with it.
Given that, it’s more useful to define “spoils” in terms of finite goods and services and look at spending on those goods and services. That is what directly affects the average person—it’s what makes housing or education or Disney tickets or whatever harder to access.
And on that front, the income growth of the top 10% has had a much more significant impact on the average person. The top 10% accounts for half of consumer spending today, up from 35% in the 1990s. And that spending is coming from the upper middle class, not billionaires. Bezos might be worth a million times more than the average person, but he’s not buying a million times more housing or Disney tickets or hotel rooms. Instead, the average person is competing directly with the increasingly affluent top 10% for access to those finite resources.
The bigger issue is weak competition. When a few companies dominate a market, they can raise prices, suppress wages, and capture more of the gains from economic growth.
That is also a big part of why wealth has become so concentrated at the top. If there were ten real cloud competitors, eight GPU makers, or several serious Office competitors, those companies would have a much harder time keeping such a large share of the profit. Instead, concentrated markets create enormous profits, and concentrated ownership turns those profits into enormous fortunes.
In my opinion, that has a bigger impact on the bottom 90%, and even on the upper middle 10% you are talking about, than the direct consumption of the top 10% ever could. It would be much better to raise the purchasing power of the bottom 90% than to reduce the consumption of the top 10%.
This is really a point that I think goes so misunderstood by so many. Yes billionaire's are bad, but people making 3x the median have a much bigger impact on those making median or less.
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> If we tax the proceeds of AI generated productivity sufficiently
That's not going to happen.
What about like a PNG tax for transparent pixels?
Transparent pixels harm the environment because they use energy and don't even do anything
I think it’s possible AI job disruption (or the threat thereof) could lead to a new labor movement capable of uniting people across the isle. It remains to be seen, but I think if the threat of a “permanent underclass” isn’t enough to get people to compromise and cooperate, nothing will.
People need to update their priors. The “permanent underclass” concern arose from a time when people thought AI was going to dominated by the first company to achieve it. But now we see that AI is becoming commoditized faster than almost any technology in recent history. IBM and Microsoft had a monopoly on personal computing for decades. AI is becoming a commodity before any of the AI companies have even turned a profit. AI is going to be like electric motors. If you had a monopoly on electric motors you could control the world! But instead they’re commodity products mass manufactured around the world
Haven't you seen how ridiculously good robots have become?
I think this is Jevon's paradox playing out in full force, and I'm quite confident we'll continue to see the growth in well paid STEM jobs despite the anecdata in this thread (anecdotally my group of ICs on tech have all seen our comp grow a lot in the last few years)
Until we saturate the demand for software which may very well be infinite
In my company several(40/200) people have are in the process of getting fired with the explanation that AI will help to fill in. I'm not convinced.
The jobs numbers have been terrible and revised down. Huge amounts of people have dropped out if the workforce or are employed in multiple part times or struggling seriously in a single full time.
I saw an article here about the job market for writers. I can't recall, but I think it was a blog post saying like "AI is bad and has annoying prose so GOOD writers will thrive". The comments rightfully pointed out that not everything requires good writing and many companies will "buy" writing for llm prices as good enough to save money.
I bring it up because that is where someone simply articulated the obvious point I hadn't really thought through: the cascade. What happens when millions of copywriters, non famous journalist, average graphic designers, etc. get laid off. Millions of people will drive the price of labor WAY down as this wage bubble wanders through industries popping every few months. If the supply if labor becomes massive, we will have this debt spiral or stagflationary labor market that causes chaos. Ultimately, capital owners accrue the most value and can buy tons of assets for cheap. Unless, it turns out a middle classes consumption is like...important for our country to function.
I would argue that AI tooling does not have a moat and would be subsumed by the Big Two labs themselves, but then Cursor happened.
Remind me what percentage of the workforce works “AI jobs”?
Well one way to look at it is:
As a programmer, but working in two non-SWE roles, I have turned job A 70% over to AI, and job B 90%.
Where systems and scaffolds can be put in place to manage various aspects of a job, would this not be considered, partially, an "AI job"?
If you work in government grants and R&D, what if agents can now triage 100-1000x the opportunity count that you could ever handle alone, and you had a pipeline system in place to manage said opportunities and relationships? And then you, as the human, become the mouthpiece and reviewer of hoards of filtered output? Is that Federal Grants & R&D position now not mostly an AI job?
I'd say a large percentage of digital-based jobs can be considered varying percentages of AI jobs.
I think they mean jobs directly related to AI, not merely exercising AI to increase productivity:
AI is also creating a new class of white-collar jobs. Engineers build the models, data annotators label their inputs and judge their answers, “forward-deployed” engineers adapt them for customers, and newly minted “heads of AI” decide what companies should do with the technology.
AI boom for jobs has always been here. Companies want to be on top of this stuff more then ever. Especially if they can replace more workers with it.
AI boosters: "look, AI is creating jobs, all of these doomers scaring you with job loses, don't listen to them"
also AI boosters: "we are going to build a million robots, and the robots will build factories producing robots, there will be infinite abundance, nobody will need to work anymore"
> there will be infinite abundance
Maybe.
> nobody will need to work anymore
If we define "nobody" as very wealthy people who partake in that abundance while everyone else ... goes away.
When AI gets that good, a solar panel can power a pile of motors and gears to move and do work for you that previously required humans. You won't need the job, you need to solve your necessities more directly. And that job is a good fit for the AI that was so good it put you out of a job.
So... robots build shit that the wealthy who own the robots can profit from it and I need to ... what? ... go grow my own potatoes if I want to live?
Okay...
Own your robot, it will cost less than a car.
First of all, cite them. Second of all, on which time scale, are they both talking about the near, mid or long terms?
unironically the second scenario sounds better
Paywalled
> On September 4th the Bureau of Labour Statistics reported that the American economy added 162,000 jobs in August, far above expectations.
Good news that ought to be taken with a pinch of salt given how the current administration responds to unfavorable BLS data -
> On Friday, August 1, [2025] President Trump fired Dr. Erika McEntarfer from her role as the Commissioner of the Bureau of Labor Statistics (BLS). In social media posts announcing and confirming her firing, he said that he believed the jobs report released by the agency earlier that day included numbers that were “rigged in order to make the Republicans, and ME, look bad.”
https://www.epi.org/policywatch/firing-bls-commissioner-erik...
The first series of "Blackadder" has a vignette of such reportage:
Messenger 3: My Lord, news…
King: What?
Messenger 3: Lord Wessex is dead.
King: This news is not so good.
Messenger 3: Pardon, My Lord?
King: I like it not. Bring me some other news.
Messenger 3: Pardon, My Lord?
King: I LIKE NOT THIS NEWS! BRING ME SOME OTHER NEWS!!!
Messenger 3: Yes, My Lord!
(Messenger 3 leaves; King tosses things around angrily; Messenger 4 enters — actually just Messenger 3 pretending to be a new messenger delivering new news.)
Messenger 4: My Lord, news…
King: What?
Messenger 4: Lord Wessex is not dead.
King: Ah, good news! Let there be joy and celebration; let jubilation reign!
Even outside of the current administration, isn't BLS data notorious for being adjusted after the fact, often downwards? Basing reporting on fresh BLS data seems ill-advised.
Yeah, it's survey based and some employers don't hit the first few deadlines.
Last month got revised to being positive, at the same time that this month was being released.
When news doesn't confirm my belief, doubt it and make sure people know.
Trust me I do the same.
Wasn’t she only in that job for a year? Maybe she was doing a bad job.
The current head of the BLS seems well qualified. Here are some select quotes from a NYT article [1]:
Now these comments were written back in January of this year.Can you cite any specific examples of wrongdoing? Or inaccurate numbers or figures outside of normal revisions?
When I see bad numbers from the BLS I say yes that’s probably true. When I see good numbers from the BLS I say yes that’s probably true.
[1] https://www.nytimes.com/2026/01/30/business/trump-bureau-of-...
Interesting how we got frank propaganda on the front page now. Pretty sad. There are no jobs. Not real jobs.
So the lore of capitalism was on point this time -- whenever one market closes, resources (you) are freed to form a new market.
I've spent 10 years implementing new technology into businesses from all over the world and the thing that has killed the most projects at the proof of concept phase has not been whether it works. It's whether the cost of going to production from PoC produces a significant ROI. AI is absolutely changing the economics there.
Humans were simply nowhere near answering all the useful questions they had which software could answer. The problem was that software was expensive.
Now, software is cheaper and so people who couldn't afford to answer questions they've long wondered about can afford to answer them.
>people who couldn't afford to answer questions they've long wondered about can afford to answer them.
If the software isn't downright free – today, you can slap a $349 RTX 5060 [†] into any POS surplus computer and have an offline assistant, running Llama or Ornith, via Ollama in linux (i.e. the LLM and OS are FREE open-source software) [∑]
I have a working demo of this that has been shown/leant to several friends, and they're all surprised that it "all works so well, without being online, for only a few hundred dollars."
When I've demonstrated Mistral-small on my 5070Ti... that has been a real jaw dropper. I haven't shown anybody qwen3.8:27b, yet... but dammmmm, what a month of learning it's been.
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A friend that was going through wifecancer confided in me that "you can ask it anything, without feeling embarassed" – and that has stuck with me (that so many smart people are afraid to ask simple questions [*], out of perceptional worries).
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[†] (8GB DDR7) brand new from Wal-Mart
[∑] My first linux/LLM machine was built with setup help from Perplexity.ai (with a dozen "assists" - I am bluecollar, non-coder). This used an obsolete i5 (and $200 used VEGA64 GPU) to create a decent Llama3.1 LLM machine (~100wpm typeback, perhaps 70 tokens/s).
[*] even to their own detriment, of shame, when simple solutions often do exist
> Now, software is cheaper and so people who couldn't afford to answer questions they've long wondered about can afford to answer them.
Temporarily. Token price will rise sharply when the bills finally come due.
No longer convinced that’s true. Some of the indebted providers might go under but there is nothing preventing someone from just setting up a new provider and serving tokens debt free. GLM or whatever.
That provides continuous downward pressure on token prices even if it isn’t Astra level
Agree model providers can't take much margin, a few percent plus maybe a bit extra from those willing to pay for a "better" model. Upstream is more concentrated: TSMC, NVIDIA, AMD could maybe raise prices and capture more of the value, which would affect open model providers.
Do you have any evidence to suggest that this true? And if so, why can't I just use any of the very good open source Chinese models (and eventually American once reflection, thinking machines, etc catch up).
Look around? It's rape and pillage time for corporations.
The Economist is just a pro-capitalist shill
This is the biggest bullshit lie ever
I haven't had a job in 4 years. Well okay I am an old piece of shit of 49 yrs old with a Stanford degree. So obsolete for this new AI world of imaginary bullshits. So I deserve it
Blatant propaganda is not an effective remedy to the severe public anti-AI sentiment, sorry.
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>The Economist, Silicon Valley's primary submarine, dispels the notion that AI causes unemployment because SV has realized that the peasants get unruly.
???
From a few months ago: https://www.economist.com/content-assets/images/20260516_DE_...
Every single aspect of that cover is manipulative marketing.
Right, but OP's implication is that they're trying to placate the masses (that somehow read the economist?), even though a few months before they were putting out alarmist covers. You can't have it both ways. If you're arguing that economist being pro-job loss is part of a globalist conspiracy and so is the economist being anti-job loss, then you just created an unfalsifiable statement, a "heads I win, tails you lose" argument.
I suspect "submarine" was meant in this sense: https://www.paulgraham.com/submarine.html
Note well: This does not mean that I agree with any part of what he said. Just explaining the term.
That was when Silicon Valley still favored the job loss narrative to drive up CEO interest for AI.
Now protests are getting louder and the midterms are close.